Emergent Properties of Gene Regulatory Networks: Models and Data

Abstract

We emphasize here the importance of generic models of biological systems that aim at describing the features that are common to a wide class of systems, instead of studying in detail a specific subsystem in a specific cell type or organism. Among generic models of gene regulatory networks, Random Boolean networks (RBNs) are reviewed in depth, and it is shown that they can accurately describe some important experimental data, in particular the statistical properties of the perturbations of gene expression levels induced by the knock-out of a single gene. It is also shown that this kind of study may shed light on a candidate general dynamical property of biological systems. Several biologically plausible modifications of the original model are reviewed and discussed, and it is also show how RBNs can be applied to describe cell differentiation.

Notes

Acknowledgments

We have developed our understanding of genetic network dynamics interacting with several scientists and collaborators. In particular, we are grateful to Stuart Kauffman who shared with us much of his insight, and of his evolving vision. Among several students and collaborators let us mention in particular Chiara Damiani, Alessandro Filisetti, Alex Graudenzi (the complete list would be too long). We also had the privilege of discussing our ideas with some biologists, in particular with Annamaria Colacci. On a more general ground, our understanding of the role of modeling such complex systems has been shaped in several fruitful discussions and joint works with David Lane and Gianni Zanarini, although of course we take full responsibility of the positions taken in this chapter. The present work has been partly supported by the Miur Project MITICA (FISR nr. 2982/Ric) and by the EU-FET projects MD (ref. 284625) and INSITE (ref. 271574) under the 7th Framework Programme.